1. Field of the Disclosure
The invention relates to a heat management method for a building and a heat system implementing such a method. It also relates to a medium comprising software implementing such a method. Finally, it also relates to a building equipped with such a heat system.
2. Related Art
It is useful to be able to forecast the energy consumption of a building to be able to anticipate the heating or the air-conditioning of the building and achieve, at any moment, the comfort desired by its occupants. However, the heat phenomena which characterize a building are complex and difficult to comprehend.
For this, a first prior art solution relies on an analysis of measured values and data stored over a long period, a year for example. Notably, the energy consumption and internal temperature values of the building are stored as a function of time, together with corresponding meteorological data such as the outside temperature and sunlight. A hybridisation based on a digital processing by a method of neural network type makes it possible to determine a mathematical model representative of these past data, which is then used to produce future forecasts. This method, based on artificial intelligence, requires a large number of data to achieve an acceptable result, which takes a long time to finalize and entails complex computations. Also, since it does not rely on a physical approach to the phenomena, it remains limited and cannot achieve sufficient accuracy in all situations.
A second prior art solution relies on a modelling of the physical phenomena based on strong simplifications so as not to require excessive computation means. In this modelling, the heat exchanges with the outside, of radiation or convection type for example, are disregarded.
In all cases, the results remain unsatisfactory and there is a need for an improved solution for forecasting the energy consumption of a building.